Suppr超能文献

α-肾上腺素能受体激动剂特异性的结构基础。

Structural basis of agonist specificity of α-adrenergic receptor.

机构信息

Department of Physiology and Biophysics, Weill Cornell Medical College of Cornell University, New York, NY, 10065, USA.

Center for Computational Biology and Department of Molecular Biosciences, University of Kansas, Lawrence, KS, 66047, USA.

出版信息

Nat Commun. 2023 Aug 10;14(1):4819. doi: 10.1038/s41467-023-40524-2.

Abstract

α-adrenergic receptors (α-ARs) play critical roles in the cardiovascular and nervous systems where they regulate blood pressure, cognition, and metabolism. However, the lack of specific agonists for all α subtypes has limited our understanding of the physiological roles of different α-AR subtypes, and led to the stagnancy in agonist-based drug development for these receptors. Here we report cryo-EM structures of α-AR in complex with heterotrimeric G-proteins and either the endogenous common agonist epinephrine or the α-AR-specific synthetic agonist A61603. These structures provide molecular insights into the mechanisms underlying the discrimination between α-AR and α-AR by A61603. Guided by the structures and corresponding molecular dynamics simulations, we engineer α-AR mutants that are not responsive to A61603, and α-AR mutants that can be potently activated by A61603. Together, these findings advance our understanding of the agonist specificity for α-ARs at the molecular level, opening the possibility of rational design of subtype-specific agonists.

摘要

α-肾上腺素能受体(α-ARs)在心血管和神经系统中发挥着关键作用,调节血压、认知和代谢。然而,缺乏所有 α 亚型的特异性激动剂限制了我们对不同 α-AR 亚型的生理作用的理解,并导致了这些受体基于激动剂的药物开发停滞不前。在这里,我们报告了 α-AR 与三聚体 G 蛋白复合物的冷冻电镜结构,以及内源性共同激动剂肾上腺素或 α-AR 特异性合成激动剂 A61603。这些结构为 A61603 区分 α-AR 和 α-AR 的机制提供了分子见解。根据这些结构和相应的分子动力学模拟,我们设计了对 A61603 无反应的 α-AR 突变体,以及可以被 A61603 有效激活的 α-AR 突变体。总之,这些发现推进了我们对 α-AR 激动剂特异性的分子水平理解,为设计亚型特异性激动剂提供了可能性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/79d7/10415349/cbc9c94ef602/41467_2023_40524_Fig1_HTML.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验